Prepare for your next Hadoop interview with these 30 essential questions and answers. This guide covers basic, intermediate, and advanced topics in Hadoop, HDFS, YARN, MapReduce, and cluster management. Suitable for freshers, candidates with 1-3 years experience, and professionals with 3-6 years in big data processing.
Basic Hadoop Interview Questions
1. What is Hadoop?
Hadoop is an open-source framework designed for distributed storage and processing of large datasets across clusters of computers using simple programming models.[1][2]
2. What are the main components of Hadoop?
The two main components are HDFS for distributed storage and YARN for resource management and job scheduling.[2][5]
3. What are the different modes in which Hadoop can run?
Hadoop runs in three modes: Standalone Mode, Pseudo-Distributed Mode, and Fully Distributed Mode.[1]
4. What is HDFS?
HDFS (Hadoop Distributed File System) is a distributed file system that provides high-throughput access to application data.[5]
5. What is the role of NameNode in HDFS?
NameNode manages the filesystem namespace and regulates access to files by clients, storing metadata about the file system.[1]
6. What is a DataNode in HDFS?
DataNode stores actual data in blocks and handles read/write requests from the filesystem client.[6]
7. What are Hadoop’s key configuration files?
The main configuration files are core-site.xml, hdfs-site.xml, mapred-site.xml, and yarn-site.xml.[1][3]
8. How does Hadoop achieve fault tolerance?
Fault tolerance is achieved through data replication across multiple nodes and the ability to re-run failed tasks.[1]
9. What is the default block size in HDFS?
The default block size in HDFS is 128 MB in Hadoop 2.x.[2]
10. What is Rack Awareness in Hadoop?
Rack Awareness is a mechanism that ensures data replication across different racks for improved fault tolerance and performance.[1]
Intermediate Hadoop Interview Questions
11. What is YARN in Hadoop?
YARN (Yet Another Resource Negotiator) is the resource management framework that separates resource management from job scheduling/monitoring.[2][5]
12. What are the components of YARN?
YARN consists of ResourceManager, NodeManager, ApplicationMaster, and Container.[6]
13. How does HDFS place data replicas across racks?
First replica on the local rack, second on a different rack, and third on the same rack as the second to balance fault tolerance and network traffic.[2]
14. What is the difference between Hadoop 1.x and Hadoop 2.x?
Hadoop 2.x introduces YARN replacing JobTracker/TaskTracker, supports larger clusters (up to 10,000 nodes), and includes HDFS Federation.[2]
| Feature | Hadoop 1.x | Hadoop 2.x |
|---|---|---|
| Resource Management | JobTracker/TaskTracker | YARN |
| Scalability | Up to 4,000 nodes | Up to 10,000 nodes |
| Block Size | 64 MB | 128 MB |
15. What is MapReduce?
MapReduce is a programming model for processing large datasets with a parallel, distributed algorithm on a cluster.[5]
16. What is Speculative Execution in Hadoop?
Speculative execution runs duplicate tasks on different nodes to mitigate slow tasks and improve job completion time.[5]
17. How do you monitor a Hadoop cluster?
Use tools like Ambari, Ganglia, or the Hadoop Web UI to monitor cluster health and performance.[1]
18. What is Kerberos in Hadoop?
Kerberos is a network authentication protocol used to secure Hadoop clusters through ticket-based authentication.[1][3]
19. How do you scale a Hadoop cluster?
Add new nodes to the cluster, update configuration files, and rebalance data using HDFS balancer.[1]
20. What causes a DataNode to go down?
DataNode can go down due to full disk, network issues, negative block size configuration, or high load from block reporting.[7]
Advanced Hadoop Interview Questions
21. How do you recover from a failed NameNode at Oracle?
Use Secondary NameNode metadata backup or start a new NameNode and restore from the latest checkpoint.[1]
22. What is Service Level Authorization in Hadoop?
Service Level Authorizations ensure only authorized users can perform administrative tasks on Hadoop services.[1]
23. How do you troubleshoot a slow-running Hadoop job at Atlassian?
Check cluster resources, examine task logs, identify data skew, and look for network bottlenecks.[1]
24. How is data encryption implemented in Hadoop?
Enable encryption at rest using HDFS configurations and encryption in transit through network security settings.[1]
25. What is Hadoop’s role-based access control (RBAC)?
RBAC assigns permissions based on user roles to ensure secure data access in the cluster.[1]
26. In a Paytm scenario, how would you handle data skew in MapReduce jobs?
Implement custom partitioners, use combiners to aggregate data early, or adjust the number of reducers.[1]
27. How do you calculate memory for NodeManager at Adobe?
Calculate total physical memory minus memory for Hadoop daemons, then allocate appropriate heap and off-heap memory.[2]
28. What happens if block size is set to negative in hdfs-site.xml at Zoho?
A negative block size causes DataNode failures and prevents successful HDFS writes.[7]
29. How do you secure sensitive data in a Swiggy Hadoop deployment?
Use HDFS encryption, mask data during ingestion, and implement Kerberos authentication with access controls.[1]
30. In a Salesforce production cluster, how do you decommission DataNodes safely?
Put DataNodes in decommissioning mode via configuration, wait for data re-replication, then remove from cluster.[6]
Master these Hadoop interview questions to demonstrate expertise across HDFS architecture, YARN resource management, security implementations, and production troubleshooting scenarios.
